# Databricks Isv Databricks Connect

> PWAF-compliant Databricks Connect (Python): PAT, OAuth M2M, OAuth U2M; serverless and classic compute. Use when building or testing Spark-over-Connect integrations.

- Skill: `databricks-solutions/databricks-isv-databricks-connect` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add databricks-solutions/databricks-isv-databricks-connect`
- Raw SKILL.md: https://api.skillmd.com/api/skills/databricks-solutions/databricks-isv-databricks-connect/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- Author: databricks-solutions (https://skillmd.com/u/databricks-solutions)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/databricks-solutions/databricks-isv-databricks-connect

---


<!-- skill-version: 1.0.0 -->

# Databricks Connect (ISV)

Use this skill when implementing or testing **Databricks Connect** (Python) for PWAF-compliant partner integrations: remote Spark execution from external apps using `databricks-connect` and `DatabricksSession`.

## Reference

- **Full patterns:** [authentication.md](authentication.md) – PAT, OAuth M2M, OAuth U2M (external-browser, localhost, token-env), serverless and classic compute, User-Agent, version compatibility, troubleshooting.

## Golden snippets (copy-paste accurate)

**Serverless PAT – Config and session with .userAgent():**
```python
from databricks.connect import DatabricksSession
from databricks.sdk.config import Config

config = Config(
    host=host_url,
    token=token,
    serverless_compute_id="auto",
)
session = (
    DatabricksSession.builder
        .sdkConfig(config)
        .userAgent("YourCompany_YourProduct/1.0.0")
        .getOrCreate()
)
```

**OAuth M2M – always set auth_type:**
```python
config = Config(
    host=host_url,
    client_id=client_id,
    client_secret=client_secret,
    auth_type="oauth-m2m",   # required
    serverless_compute_id="auto",
)
session = (
    DatabricksSession.builder
        .sdkConfig(config)
        .userAgent("YourCompany_YourProduct/1.0.0")
        .getOrCreate()
)
```

**U2M – get token first (e.g. external-browser), then Config with token:** Same as PAT but `token=access_token` from browser flow. For external-browser, unset `DATABRICKS_CLIENT_ID`/`DATABRICKS_CLIENT_SECRET` before calling SDK.

## Requirements

- **User-Agent (required):** Use `.userAgent("<isv>_<product>/<version>")` on `DatabricksSession.builder` (PWAF-recommended). Do not expose as user config. See [PWAF Databricks Connect telemetry](https://databrickslabs.github.io/partner-architecture/isv-partners/telemetry-attribution/databricks-connect).
- **Auth types:** Support PAT, OAuth M2M, and OAuth U2M. One connection = one auth type; do not set both PAT and M2M (or U2M) vars in the same process.
- **OAuth M2M:** Always pass `auth_type="oauth-m2m"` to `Config(...)` when using `client_id`/`client_secret` so the SDK does not run default credential resolution.

## Compute options

- **Serverless (recommended):** `DATABRICKS_SERVERLESS_COMPUTE_ID=auto` or `Config(..., serverless_compute_id="auto")`. No cluster to manage. Some Connect versions do not yet support serverless; in that case use classic.
- **Classic:** `DATABRICKS_CLUSTER_ID` or `CLASSIC_COMPUTE_HTTP_PATH` (cluster ID = last path segment, e.g. `sql/protocolv1/o/<workspace_id>/<cluster_id>`).
- **Rule:** Do not set both serverless and classic in the same env; Config errors with "Can't set both cluster id and serverless_compute_id".

## U2M with Connect

Obtain an **access token first**, then pass it to `Config(host=..., token=access_token, ...)` for `DatabricksSession`. Same three flows as REST/SQL U2M:

| Flow | Use when | Required |
|------|----------|----------|
| **external-browser** | No custom OAuth app; SDK opens browser | `DATABRICKS_HOST`; unset `DATABRICKS_CLIENT_ID`/`DATABRICKS_CLIENT_SECRET`/`DATABRICKS_TOKEN` so SDK uses built-in app |
| **localhost** | Custom OAuth app with localhost redirect | `DATABRICKS_HOST`, `DATABRICKS_CLIENT_ID` (OAuth app, not M2M); optional redirect_uri, client_secret |
| **token-env** | Pre-obtained token (no browser) | `DATABRICKS_HOST`, `DATABRICKS_ACCESS_TOKEN` or `DATABRICKS_TOKEN` |

**Important:** M2M service principal `client_id` is not valid for browser U2M. For external-browser, do not pass client_id. For localhost, use a separate OAuth custom app.

## Version compatibility

- `databricks-connect` version must match the Databricks Runtime (DBR) on compute (e.g. DBR 18 → `databricks-connect==18.0.*`).
- Do not install PySpark separately; databricks-connect supplies the matching Spark stack.

## Auth isolation

Run each test or script with a **clean environment**: only the vars for the chosen auth type and compute. Use `env -i` plus explicit vars when running tests so PAT, M2M, and U2M do not mix (avoids "more than one authorization method configured").

## Validation

- Build `DatabricksSession` with the chosen auth and compute; run a simple read (e.g. `spark.table("samples.nyctaxi.trips").count()`) to verify connection and permissions.